YData Profiling Report

Dataset statistics

Number of variables	17
Number of observations	20000
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	9.1 MiB
Average record size in memory	474.7 B

Variable types

Text	1
Categorical	7
Numeric	8
Boolean	1

Alerts

`years_of_employment` has 550 (2.8%) zeros	Zeros

Reproduction

Analysis started	2026-02-11 10:35:18.397197
Analysis finished	2026-02-11 10:35:28.734956
Duration	10.34 seconds
Software version	ydata-profiling vv4.18.1
Download configuration	config.json

name
Text

Distinct	200
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

Length

Max length	14
Median length	13
Mean length	11.05745
Min length	8

Characters and Unicode

Total characters	221149
Distinct characters	30
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Vihaan Sharma
2nd row	Ishaan Patel
3rd row	Krishna Gupta
4th row	Vihaan Singh
5th row	Aditya Mehta

Value	Count	Frequency (%)
iyer	2085	5.2%
gupta	2050	5.1%
sharma	2033	5.1%
khan	2023	5.1%
mehta	2018	5.0%
reddy	1994	5.0%
singh	1986	5.0%
patel	1960	4.9%
nair	1943	4.9%
verma	1908	4.8%
Other values (20)	20000	50.0%

Most occurring characters

Value	Count	Frequency (%)
a	42935	19.4%
	20000	9.0%
n	15099	6.8%
i	14992	6.8%
r	14953	6.8%
h	14038	6.3%
y	13045	5.9%
e	10948	5.0%
S	7943	3.6%
t	7089	3.2%
Other values (20)	60107	27.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	221149	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	42935	19.4%
	20000	9.0%
n	15099	6.8%
i	14992	6.8%
r	14953	6.8%
h	14038	6.3%
y	13045	5.9%
e	10948	5.0%
S	7943	3.6%
t	7089	3.2%
Other values (20)	60107	27.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	221149	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	42935	19.4%
	20000	9.0%
n	15099	6.8%
i	14992	6.8%
r	14953	6.8%
h	14038	6.3%
y	13045	5.9%
e	10948	5.0%
S	7943	3.6%
t	7089	3.2%
Other values (20)	60107	27.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	221149	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	42935	19.4%
	20000	9.0%
n	15099	6.8%
i	14992	6.8%
r	14953	6.8%
h	14038	6.3%
y	13045	5.9%
e	10948	5.0%
S	7943	3.6%
t	7089	3.2%
Other values (20)	60107	27.2%

identification_through
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

Driving License	5108
Passport	5015
Aadhar	5010
PAN	4867

Length

Max length	15
Median length	8
Mean length	8.07005
Min length	3

Characters and Unicode

Total characters	161401
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	PAN
2nd row	PAN
3rd row	Aadhar
4th row	PAN
5th row	PAN

Common Values

Value	Count	Frequency (%)
Driving License	5108	25.5%
Passport	5015	25.1%
Aadhar	5010	25.1%
PAN	4867	24.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
driving	5108	20.3%
license	5108	20.3%
passport	5015	20.0%
aadhar	5010	20.0%
pan	4867	19.4%

Most occurring characters

Value	Count	Frequency (%)
i	15324	9.5%
s	15138	9.4%
r	15133	9.4%
a	15035	9.3%
e	10216	6.3%
n	10216	6.3%
P	9882	6.1%
A	9877	6.1%
v	5108	3.2%
D	5108	3.2%
Other values (10)	50364	31.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	161401	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	15324	9.5%
s	15138	9.4%
r	15133	9.4%
a	15035	9.3%
e	10216	6.3%
n	10216	6.3%
P	9882	6.1%
A	9877	6.1%
v	5108	3.2%
D	5108	3.2%
Other values (10)	50364	31.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	161401	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	15324	9.5%
s	15138	9.4%
r	15133	9.4%
a	15035	9.3%
e	10216	6.3%
n	10216	6.3%
P	9882	6.1%
A	9877	6.1%
v	5108	3.2%
D	5108	3.2%
Other values (10)	50364	31.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	161401	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	15324	9.5%
s	15138	9.4%
r	15133	9.4%
a	15035	9.3%
e	10216	6.3%
n	10216	6.3%
P	9882	6.1%
A	9877	6.1%
v	5108	3.2%
D	5108	3.2%
Other values (10)	50364	31.2%

cibil_score
Real number (ℝ)

Distinct	601
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	600.78785

Minimum	300
Maximum	900
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	300
5-th percentile	329
Q1	449
median	600
Q3	753
95-th percentile	872
Maximum	900
Range	600
Interquartile range (IQR)	304

Descriptive statistics

Standard deviation	174.34704
Coefficient of variation (CV)	0.29019735
Kurtosis	-1.2127606
Mean	600.78785
Median Absolute Deviation (MAD)	152
Skewness	0.0038428634
Sum	12015757
Variance	30396.892
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
411	55	0.3%
719	54	0.3%
432	47	0.2%
368	47	0.2%
740	47	0.2%
576	47	0.2%
859	47	0.2%
727	46	0.2%
410	46	0.2%
572	46	0.2%
Other values (591)	19518	97.6%

Value	Count	Frequency (%)
300	42	0.2%
301	28	0.1%
302	30	0.1%
303	24	0.1%
304	27	0.1%
305	25	0.1%
306	29	0.1%
307	37	0.2%
308	30	0.1%
309	38	0.2%

Value	Count	Frequency (%)
900	41	0.2%
899	28	0.1%
898	43	0.2%
897	36	0.2%
896	32	0.2%
895	37	0.2%
894	31	0.2%
893	30	0.1%
892	24	0.1%
891	36	0.2%

age
Real number (ℝ)

Distinct	44
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	42.53995

Minimum	21
Maximum	64
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	21
5-th percentile	23
Q1	32
median	43
Q3	53
95-th percentile	62
Maximum	64
Range	43
Interquartile range (IQR)	21

Descriptive statistics

Standard deviation	12.660755
Coefficient of variation (CV)	0.29762036
Kurtosis	-1.1949317
Mean	42.53995
Median Absolute Deviation (MAD)	11
Skewness	0.00094946869
Sum	850799
Variance	160.29472
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=44)

Value	Count	Frequency (%)
58	494	2.5%
50	489	2.4%
33	489	2.4%
47	485	2.4%
43	479	2.4%
49	479	2.4%
31	477	2.4%
25	477	2.4%
61	476	2.4%
46	474	2.4%
Other values (34)	15181	75.9%

Value	Count	Frequency (%)
21	417	2.1%
22	454	2.3%
23	445	2.2%
24	469	2.3%
25	477	2.4%
26	428	2.1%
27	456	2.3%
28	437	2.2%
29	445	2.2%
30	438	2.2%

Value	Count	Frequency (%)
64	468	2.3%
63	416	2.1%
62	460	2.3%
61	476	2.4%
60	458	2.3%
59	460	2.3%
58	494	2.5%
57	466	2.3%
56	437	2.2%
55	449	2.2%

annual_income
Real number (ℝ)

Distinct	19912
Distinct (%)	99.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1360189.6

Minimum	200073
Maximum	2499681
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	200073
5-th percentile	313902.25
Q1	785526.25
median	1369203
Q3	1934202.8
95-th percentile	2387104.4
Maximum	2499681
Range	2299608
Interquartile range (IQR)	1148676.5

Descriptive statistics

Standard deviation	665740.28
Coefficient of variation (CV)	0.48944667
Kurtosis	-1.2034797
Mean	1360189.6
Median Absolute Deviation (MAD)	574452
Skewness	-0.026908375
Sum	2.7203792 × 10¹⁰
Variance	4.4321011 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1361538	3	< 0.1%
734975	2	< 0.1%
2005331	2	< 0.1%
1245401	2	< 0.1%
1659603	2	< 0.1%
1551934	2	< 0.1%
1522263	2	< 0.1%
1875984	2	< 0.1%
216625	2	< 0.1%
2124651	2	< 0.1%
Other values (19902)	19979	99.9%

Value	Count	Frequency (%)
200073	1	< 0.1%
200116	1	< 0.1%
200133	1	< 0.1%
200409	1	< 0.1%
200435	1	< 0.1%
201282	1	< 0.1%
201286	1	< 0.1%
201699	1	< 0.1%
201759	1	< 0.1%
201773	1	< 0.1%

Value	Count	Frequency (%)
2499681	1	< 0.1%
2499582	1	< 0.1%
2499506	1	< 0.1%
2499353	1	< 0.1%
2499141	1	< 0.1%
2498925	2	< 0.1%
2498881	1	< 0.1%
2498865	1	< 0.1%
2498819	1	< 0.1%
2498693	1	< 0.1%

employment_type
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

Self-Employed	6744
Salaried	6669
Business	6587

Length

Max length	13
Median length	8
Mean length	9.686
Min length	8

Characters and Unicode

Total characters	193720
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Self-Employed
2nd row	Salaried
3rd row	Salaried
4th row	Salaried
5th row	Self-Employed

Common Values

Value	Count	Frequency (%)
Self-Employed	6744	33.7%
Salaried	6669	33.3%
Business	6587	32.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
self-employed	6744	33.7%
salaried	6669	33.3%
business	6587	32.9%

Most occurring characters

Value	Count	Frequency (%)
e	26744	13.8%
l	20157	10.4%
s	19761	10.2%
S	13413	6.9%
d	13413	6.9%
a	13338	6.9%
i	13256	6.8%
f	6744	3.5%
-	6744	3.5%
E	6744	3.5%
Other values (8)	53406	27.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	193720	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	26744	13.8%
l	20157	10.4%
s	19761	10.2%
S	13413	6.9%
d	13413	6.9%
a	13338	6.9%
i	13256	6.8%
f	6744	3.5%
-	6744	3.5%
E	6744	3.5%
Other values (8)	53406	27.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	193720	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	26744	13.8%
l	20157	10.4%
s	19761	10.2%
S	13413	6.9%
d	13413	6.9%
a	13338	6.9%
i	13256	6.8%
f	6744	3.5%
-	6744	3.5%
E	6744	3.5%
Other values (8)	53406	27.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	193720	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	26744	13.8%
l	20157	10.4%
s	19761	10.2%
S	13413	6.9%
d	13413	6.9%
a	13338	6.9%
i	13256	6.8%
f	6744	3.5%
-	6744	3.5%
E	6744	3.5%
Other values (8)	53406	27.6%

years_of_employment
Real number (ℝ)

Zeros

Distinct	40
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	19.56895

Minimum	0
Maximum	39
Zeros	550
Zeros (%)	2.8%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	10
median	20
Q3	30
95-th percentile	38
Maximum	39
Range	39
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	11.563037
Coefficient of variation (CV)	0.59088695
Kurtosis	-1.1993497
Mean	19.56895
Median Absolute Deviation (MAD)	10
Skewness	-0.013179532
Sum	391379
Variance	133.70383
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
0	550	2.8%
26	535	2.7%
32	527	2.6%
25	526	2.6%
4	525	2.6%
29	525	2.6%
37	524	2.6%
38	522	2.6%
10	518	2.6%
11	516	2.6%
Other values (30)	14732	73.7%

Value	Count	Frequency (%)
0	550	2.8%
1	508	2.5%
2	480	2.4%
3	456	2.3%
4	525	2.6%
5	456	2.3%
6	487	2.4%
7	477	2.4%
8	508	2.5%
9	503	2.5%

Value	Count	Frequency (%)
39	498	2.5%
38	522	2.6%
37	524	2.6%
36	507	2.5%
35	467	2.3%
34	486	2.4%
33	493	2.5%
32	527	2.6%
31	499	2.5%
30	492	2.5%

existing_loans
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	976.7 KiB

3	4092
4	4078
1	3996
2	3938
0	3896

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	20000
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	2
3rd row	2
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
3	4092	20.5%
4	4078	20.4%
1	3996	20.0%
2	3938	19.7%
0	3896	19.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
3	4092	20.5%
4	4078	20.4%
1	3996	20.0%
2	3938	19.7%
0	3896	19.5%

Most occurring characters

Value	Count	Frequency (%)
3	4092	20.5%
4	4078	20.4%
1	3996	20.0%
2	3938	19.7%
0	3896	19.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	20000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
3	4092	20.5%
4	4078	20.4%
1	3996	20.0%
2	3938	19.7%
0	3896	19.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	20000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
3	4092	20.5%
4	4078	20.4%
1	3996	20.0%
2	3938	19.7%
0	3896	19.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	20000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
3	4092	20.5%
4	4078	20.4%
1	3996	20.0%
2	3938	19.7%
0	3896	19.5%

loan_amount
Real number (ℝ)

Distinct	19894
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1024454.7

Minimum	50086
Maximum	1999987
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	50086
5-th percentile	147329.2
Q1	531797.5
median	1022587.5
Q3	1520187.8
95-th percentile	1905603.9
Maximum	1999987
Range	1949901
Interquartile range (IQR)	988390.25

Descriptive statistics

Standard deviation	565980.48
Coefficient of variation (CV)	0.55246999
Kurtosis	-1.2160945
Mean	1024454.7
Median Absolute Deviation (MAD)	493617
Skewness	0.0019372338
Sum	2.0489094 × 10¹⁰
Variance	3.203339 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1336330	2	< 0.1%
1024712	2	< 0.1%
152549	2	< 0.1%
899980	2	< 0.1%
841213	2	< 0.1%
668841	2	< 0.1%
1260912	2	< 0.1%
1249473	2	< 0.1%
1908048	2	< 0.1%
1897361	2	< 0.1%
Other values (19884)	19980	99.9%

Value	Count	Frequency (%)
50086	1	< 0.1%
50231	1	< 0.1%
50448	1	< 0.1%
50497	1	< 0.1%
50641	1	< 0.1%
51035	1	< 0.1%
51191	1	< 0.1%
51241	1	< 0.1%
51453	1	< 0.1%
51489	1	< 0.1%

Value	Count	Frequency (%)
1999987	1	< 0.1%
1999858	1	< 0.1%
1999851	1	< 0.1%
1999836	1	< 0.1%
1999771	1	< 0.1%
1999748	1	< 0.1%
1999740	1	< 0.1%
1999501	1	< 0.1%
1999467	1	< 0.1%
1999290	1	< 0.1%

loan_tenure_years
Real number (ℝ)

Distinct	29
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14.97795

Minimum	1
Maximum	29
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	8
median	15
Q3	22
95-th percentile	28
Maximum	29
Range	28
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	8.3513503
Coefficient of variation (CV)	0.55757632
Kurtosis	-1.1992982
Mean	14.97795
Median Absolute Deviation (MAD)	7
Skewness	-0.0016007385
Sum	299559
Variance	69.745051
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=29)

Value	Count	Frequency (%)
10	720	3.6%
8	719	3.6%
5	719	3.6%
1	719	3.6%
23	712	3.6%
18	710	3.5%
11	709	3.5%
21	708	3.5%
16	707	3.5%
6	707	3.5%
Other values (19)	12870	64.3%

Value	Count	Frequency (%)
1	719	3.6%
2	682	3.4%
3	658	3.3%
4	677	3.4%
5	719	3.6%
6	707	3.5%
7	645	3.2%
8	719	3.6%
9	659	3.3%
10	720	3.6%

Value	Count	Frequency (%)
29	660	3.3%
28	684	3.4%
27	689	3.4%
26	689	3.4%
25	691	3.5%
24	685	3.4%
23	712	3.6%
22	664	3.3%
21	708	3.5%
20	675	3.4%

interest_rate
Real number (ℝ)

Distinct	1101
Distinct (%)	5.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12.469395

Minimum	7
Maximum	18
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	7
5-th percentile	7.52
Q1	9.7075
median	12.44
Q3	15.21
95-th percentile	17.45
Maximum	18
Range	11
Interquartile range (IQR)	5.5025

Descriptive statistics

Standard deviation	3.1874127
Coefficient of variation (CV)	0.25561886
Kurtosis	-1.2002985
Mean	12.469395
Median Absolute Deviation (MAD)	2.76
Skewness	0.009684857
Sum	249387.91
Variance	10.159599
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11.09	32	0.2%
14.67	31	0.2%
14.52	31	0.2%
13.5	31	0.2%
14.09	30	0.1%
10.35	30	0.1%
7.94	29	0.1%
17.54	29	0.1%
13.42	29	0.1%
15.76	29	0.1%
Other values (1091)	19699	98.5%

Value	Count	Frequency (%)
7	10	0.1%
7.01	18	0.1%
7.02	17	0.1%
7.03	13	0.1%
7.04	9	< 0.1%
7.05	17	0.1%
7.06	25	0.1%
7.07	26	0.1%
7.08	17	0.1%
7.09	17	0.1%

Value	Count	Frequency (%)
18	11	0.1%
17.99	21	0.1%
17.98	22	0.1%
17.97	17	0.1%
17.96	22	0.1%
17.95	17	0.1%
17.94	26	0.1%
17.93	13	0.1%
17.92	16	0.1%
17.91	17	0.1%

debt_to_income_ratio
Real number (ℝ)

Distinct	51
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.350266

Minimum	0.1
Maximum	0.6
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	0.1
5-th percentile	0.13
Q1	0.23
median	0.35
Q3	0.48
95-th percentile	0.57
Maximum	0.6
Range	0.5
Interquartile range (IQR)	0.25

Descriptive statistics

Standard deviation	0.14417104
Coefficient of variation (CV)	0.41160444
Kurtosis	-1.2054238
Mean	0.350266
Median Absolute Deviation (MAD)	0.13
Skewness	-0.0011783475
Sum	7005.32
Variance	0.020785289
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.56	448	2.2%
0.55	441	2.2%
0.57	432	2.2%
0.25	431	2.2%
0.27	426	2.1%
0.34	425	2.1%
0.48	422	2.1%
0.17	420	2.1%
0.22	420	2.1%
0.4	417	2.1%
Other values (41)	15718	78.6%

Value	Count	Frequency (%)
0.1	197	1.0%
0.11	397	2.0%
0.12	384	1.9%
0.13	397	2.0%
0.14	355	1.8%
0.15	410	2.1%
0.16	417	2.1%
0.17	420	2.1%
0.18	411	2.1%
0.19	380	1.9%

Value	Count	Frequency (%)
0.6	176	0.9%
0.59	379	1.9%
0.58	362	1.8%
0.57	432	2.2%
0.56	448	2.2%
0.55	441	2.2%
0.54	380	1.9%
0.53	391	2.0%
0.52	409	2.0%
0.51	409	2.0%

marital_status
Categorical

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

Single	6747
Married	6640
Divorced	6613

Length

Max length	8
Median length	7
Mean length	6.9933
Min length	6

Characters and Unicode

Total characters	139866
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Divorced
2nd row	Married
3rd row	Single
4th row	Divorced
5th row	Divorced

Common Values

Value	Count	Frequency (%)
Single	6747	33.7%
Married	6640	33.2%
Divorced	6613	33.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
single	6747	33.7%
married	6640	33.2%
divorced	6613	33.1%

Most occurring characters

Value	Count	Frequency (%)
i	20000	14.3%
e	20000	14.3%
r	19893	14.2%
d	13253	9.5%
S	6747	4.8%
n	6747	4.8%
l	6747	4.8%
g	6747	4.8%
a	6640	4.7%
M	6640	4.7%
Other values (4)	26452	18.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	139866	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	20000	14.3%
e	20000	14.3%
r	19893	14.2%
d	13253	9.5%
S	6747	4.8%
n	6747	4.8%
l	6747	4.8%
g	6747	4.8%
a	6640	4.7%
M	6640	4.7%
Other values (4)	26452	18.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	139866	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	20000	14.3%
e	20000	14.3%
r	19893	14.2%
d	13253	9.5%
S	6747	4.8%
n	6747	4.8%
l	6747	4.8%
g	6747	4.8%
a	6640	4.7%
M	6640	4.7%
Other values (4)	26452	18.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	139866	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	20000	14.3%
e	20000	14.3%
r	19893	14.2%
d	13253	9.5%
S	6747	4.8%
n	6747	4.8%
l	6747	4.8%
g	6747	4.8%
a	6640	4.7%
M	6640	4.7%
Other values (4)	26452	18.9%

education_level
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

PhD	5071
Master	5036
Bachelor	4973
High School	4920

Length

Max length	11
Median length	8
Mean length	6.96665
Min length	3

Characters and Unicode

Total characters	139333
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Bachelor
2nd row	Master
3rd row	Bachelor
4th row	Master
5th row	Bachelor

Common Values

Value	Count	Frequency (%)
PhD	5071	25.4%
Master	5036	25.2%
Bachelor	4973	24.9%
High School	4920	24.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
phd	5071	20.3%
master	5036	20.2%
bachelor	4973	20.0%
high	4920	19.7%
school	4920	19.7%

Most occurring characters

Value	Count	Frequency (%)
h	19884	14.3%
o	14813	10.6%
r	10009	7.2%
a	10009	7.2%
e	10009	7.2%
c	9893	7.1%
l	9893	7.1%
P	5071	3.6%
D	5071	3.6%
s	5036	3.6%
Other values (8)	39645	28.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	139333	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
h	19884	14.3%
o	14813	10.6%
r	10009	7.2%
a	10009	7.2%
e	10009	7.2%
c	9893	7.1%
l	9893	7.1%
P	5071	3.6%
D	5071	3.6%
s	5036	3.6%
Other values (8)	39645	28.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	139333	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
h	19884	14.3%
o	14813	10.6%
r	10009	7.2%
a	10009	7.2%
e	10009	7.2%
c	9893	7.1%
l	9893	7.1%
P	5071	3.6%
D	5071	3.6%
s	5036	3.6%
Other values (8)	39645	28.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	139333	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
h	19884	14.3%
o	14813	10.6%
r	10009	7.2%
a	10009	7.2%
e	10009	7.2%
c	9893	7.1%
l	9893	7.1%
P	5071	3.6%
D	5071	3.6%
s	5036	3.6%
Other values (8)	39645	28.5%

property_owner
Boolean

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	19.7 KiB

True	10071
False	9929

Value	Count	Frequency (%)
True	10071	50.4%
False	9929	49.6%

loan_purpose
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.1 MiB

Home	4052
Business	4034
Education	4020
Car	3974
Personal	3920

Length

Max length	9
Median length	8
Mean length	6.3971
Min length	3

Characters and Unicode

Total characters	127942
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Education
2nd row	Business
3rd row	Home
4th row	Car
5th row	Home

Common Values

Value	Count	Frequency (%)
Home	4052	20.3%
Business	4034	20.2%
Education	4020	20.1%
Car	3974	19.9%
Personal	3920	19.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
home	4052	20.3%
business	4034	20.2%
education	4020	20.1%
car	3974	19.9%
personal	3920	19.6%

Most occurring characters

Value	Count	Frequency (%)
s	16022	12.5%
e	12006	9.4%
o	11992	9.4%
n	11974	9.4%
a	11914	9.3%
i	8054	6.3%
u	8054	6.3%
r	7894	6.2%
H	4052	3.2%
m	4052	3.2%
Other values (8)	31928	25.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	127942	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
s	16022	12.5%
e	12006	9.4%
o	11992	9.4%
n	11974	9.4%
a	11914	9.3%
i	8054	6.3%
u	8054	6.3%
r	7894	6.2%
H	4052	3.2%
m	4052	3.2%
Other values (8)	31928	25.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	127942	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
s	16022	12.5%
e	12006	9.4%
o	11992	9.4%
n	11974	9.4%
a	11914	9.3%
i	8054	6.3%
u	8054	6.3%
r	7894	6.2%
H	4052	3.2%
m	4052	3.2%
Other values (8)	31928	25.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	127942	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
s	16022	12.5%
e	12006	9.4%
o	11992	9.4%
n	11974	9.4%
a	11914	9.3%
i	8054	6.3%
u	8054	6.3%
r	7894	6.2%
H	4052	3.2%
m	4052	3.2%
Other values (8)	31928	25.0%

loan_default
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	976.7 KiB

0	15995
1	4005

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	20000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	15995	80.0%
1	4005	20.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	15995	80.0%
1	4005	20.0%

Most occurring characters

Value	Count	Frequency (%)
0	15995	80.0%
1	4005	20.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	20000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	15995	80.0%
1	4005	20.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	20000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	15995	80.0%
1	4005	20.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	20000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	15995	80.0%
1	4005	20.0%

	age	annual_income	cibil_score	debt_to_income_ratio	education_level	employment_type	existing_loans	identification_through	interest_rate	loan_amount	loan_default	loan_purpose	loan_tenure_years	marital_status	property_owner	years_of_employment
age	1.000	-0.004	0.002	-0.005	0.000	0.000	0.000	0.000	-0.005	0.005	0.000	0.000	-0.005	0.000	0.008	0.001
annual_income	-0.004	1.000	-0.007	0.003	0.017	0.000	0.000	0.006	-0.004	-0.000	0.000	0.004	-0.007	0.000	0.005	0.004
cibil_score	0.002	-0.007	1.000	-0.005	0.000	0.015	0.008	0.015	-0.001	0.005	0.005	0.011	0.011	0.000	0.021	-0.002
debt_to_income_ratio	-0.005	0.003	-0.005	1.000	0.006	0.000	0.000	0.000	0.001	-0.002	0.007	0.000	0.014	0.000	0.016	0.004
education_level	0.000	0.017	0.000	0.006	1.000	0.000	0.010	0.000	0.000	0.000	0.000	0.007	0.012	0.000	0.000	0.007
employment_type	0.000	0.000	0.015	0.000	0.000	1.000	0.012	0.000	0.000	0.009	0.000	0.000	0.000	0.000	0.005	0.010
existing_loans	0.000	0.000	0.008	0.000	0.010	0.012	1.000	0.000	0.000	0.003	0.000	0.009	0.000	0.000	0.019	0.000
identification_through	0.000	0.006	0.015	0.000	0.000	0.000	0.000	1.000	0.006	0.013	0.000	0.006	0.008	0.006	0.004	0.004
interest_rate	-0.005	-0.004	-0.001	0.001	0.000	0.000	0.000	0.006	1.000	0.000	0.000	0.010	-0.002	0.005	0.015	0.006
loan_amount	0.005	-0.000	0.005	-0.002	0.000	0.009	0.003	0.013	0.000	1.000	0.000	0.006	-0.005	0.014	0.000	0.000
loan_default	0.000	0.000	0.005	0.007	0.000	0.000	0.000	0.000	0.000	0.000	1.000	0.005	0.000	0.004	0.000	0.006
loan_purpose	0.000	0.004	0.011	0.000	0.007	0.000	0.009	0.006	0.010	0.006	0.005	1.000	0.016	0.007	0.000	0.015
loan_tenure_years	-0.005	-0.007	0.011	0.014	0.012	0.000	0.000	0.008	-0.002	-0.005	0.000	0.016	1.000	0.005	0.012	0.002
marital_status	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.006	0.005	0.014	0.004	0.007	0.005	1.000	0.000	0.008
property_owner	0.008	0.005	0.021	0.016	0.000	0.005	0.019	0.004	0.015	0.000	0.000	0.000	0.012	0.000	1.000	0.014
years_of_employment	0.001	0.004	-0.002	0.004	0.007	0.010	0.000	0.004	0.006	0.000	0.006	0.015	0.002	0.008	0.014	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

	name	identification_through	cibil_score	age	annual_income	employment_type	years_of_employment	existing_loans	loan_amount	loan_tenure_years	interest_rate	debt_to_income_ratio	marital_status	education_level	property_owner	loan_purpose	loan_default
0	Vihaan Sharma	PAN	402	25	1698527	Self-Employed	25	0	1187279	7	13.54	0.19	Divorced	Bachelor	Yes	Education	0
1	Ishaan Patel	PAN	735	44	1087238	Salaried	15	2	688217	11	11.34	0.58	Married	Master	Yes	Business	0
2	Krishna Gupta	Aadhar	570	50	929749	Salaried	11	2	692575	11	13.82	0.37	Single	Bachelor	Yes	Home	0
3	Vihaan Singh	PAN	406	50	422413	Salaried	15	1	268830	20	15.60	0.13	Divorced	Master	No	Car	0
4	Aditya Mehta	PAN	371	59	1268052	Self-Employed	33	1	367206	29	7.22	0.49	Divorced	Bachelor	Yes	Home	0
5	Ananya Sharma	Driving License	320	57	949120	Salaried	26	0	1475129	14	10.91	0.60	Divorced	Master	No	Personal	1
6	Aarav Verma	PAN	421	53	689282	Business	24	4	593124	25	10.86	0.17	Married	Bachelor	Yes	Business	0
7	Reyansh Patel	PAN	766	40	2226974	Business	18	2	109452	4	16.90	0.11	Married	Master	Yes	Education	0
8	Siya Mehta	Driving License	514	42	2244970	Self-Employed	6	1	1424506	15	17.97	0.37	Divorced	High School	Yes	Business	1
9	Aarav Singh	Driving License	630	61	731596	Business	11	3	543583	11	14.18	0.13	Divorced	Bachelor	Yes	Home	0

	name	identification_through	cibil_score	age	annual_income	employment_type	years_of_employment	existing_loans	loan_amount	loan_tenure_years	interest_rate	debt_to_income_ratio	marital_status	education_level	property_owner	loan_purpose	loan_default
19990	Arjun Nair	PAN	428	54	1672161	Business	25	2	96236	13	12.13	0.56	Married	PhD	Yes	Business	0
19991	Ishaan Gupta	Aadhar	735	43	1677126	Salaried	15	1	687203	23	12.82	0.20	Married	Bachelor	Yes	Personal	0
19992	Ananya Nair	Passport	579	35	1260454	Business	14	2	1019153	13	7.47	0.23	Single	Master	No	Home	0
19993	Shaurya Verma	Driving License	657	47	1750488	Salaried	17	1	531347	3	9.57	0.28	Married	PhD	No	Home	0
19994	Ananya Singh	PAN	551	22	1373483	Salaried	39	0	218621	14	14.10	0.60	Married	High School	Yes	Education	0
19995	Riya Patel	Aadhar	434	48	465897	Business	17	1	1123426	13	14.31	0.48	Married	High School	Yes	Personal	1
19996	Riya Gupta	PAN	822	31	1154778	Salaried	34	3	436729	16	13.68	0.38	Divorced	PhD	No	Car	0
19997	Myra Iyer	Passport	618	41	1774308	Business	4	4	1315039	25	9.26	0.43	Divorced	Bachelor	No	Home	1
19998	Krishna Mehta	Passport	379	62	206630	Business	1	3	1073667	22	11.59	0.13	Single	High School	Yes	Home	0
19999	Anika Nair	PAN	490	52	1305701	Salaried	29	1	769648	1	12.78	0.33	Divorced	Master	No	Personal	0

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)